The 50 most-cited articles in Electronics Letters, 2023

Abstract In this Letter, the authors present a novel imaging algorithm for multireceiver synthetic aperture sonar (SAS). The Loffeld's bistatic formula (LBF) including quasi‐monostatic (QM) and multireceiver deformation (MD) phases is first reformulated into range‐variant and range‐invariant phases. After compensating the range‐invariant phase, the subsequent steps are the extended Stolt mapping for each bistatic SAS. Based on simulations, the presented method can also provide high‐resolution result which is similar to that of back projection (BP) algorithm.

Abstract It is demonstrated that combining phased array antennas with dielectric lenses constitutes a suitable solution to increase the energy efficiency in next‐generation communication systems. A dielectric lens is designed to increase the gain of an array antenna working in the 3GPP n257 band (26.5–29.5 GHz). The simulated results demonstrate that the dielectric lens increases the gain between 0.4 and 1.3 dB in a large scanning range from 0° to 60° at 28 GHz; meaning that the output RF power can be decreased by up to 26% for a same equivalent isotropic radiated power required from the base station.

Abstract In this letter, a planar cavity‐backed multiplexing antenna (SMA) is proposed and validated experimentally. A planar cavity is realized by using a novel transmission line known as substrate‐integrated waveguide (SIW) technology. The design comprises five SIW cavities and each one consisting of a slot for launching the energy in free space. Three different types of slots are employed for lower mutual coupling and compact circuit integration. The individual feeds are created in such a way, that antenna produces five distinct resonant frequencies in the dominant mode while maintaining sufficient mutual port isolation. Finally, the proposed concept is validated with experiments and results show acceptable agreement with the simulated counterparts. The design shows five operating frequency channels with center frequencies of 5.2, 5.5, 5.75, 6.2, and 6.8 GHz. The mutual isolation between any two radiating elements retains below −21 dB and the average gain of the antenna is better than 3.5 dBi at each resonant frequency. The proposed SMA element can be used to cover a wide range…

Abstract A fast beam‐steering capability has been demonstrated using an array of high‐gain corrugated substrate integrated waveguide (CSIW) slot antennas coupled with a bespoke dielectric lens. The proposed system prototype has been simulated, fabricated, and measured. The proposed system is shown to have a full 360° beam‐steer in azimuth plane with an angular sensitivity of 9°, half power beamwidth (HPBW) of 18° and a gain of < 20.5 dBi at n257 frequency band of 26 to 29 GHz. Further, the antenna is shown to have a fixed frequency beam steer of ±15° along with a frequency‐controlled beam‐scanning of ±45° in the elevation plane. The antenna setup is shown to be suitable for applications for 5G base‐stations.

Abstract Robots with telepresence capabilities are typically employed for tasks where human presence is not feasible due to geography, safety risks like fire or radiation exposure, or other factors like any epidemic disease. Time delay is a significant consideration in controlling a telepresence robot. This study proposes a deep learning‐based approach to compensate for the delay by predicting the behaviour of the teleoperator. The authors integrate a recurrent neural network (RNN) based on the Long Short‐Term Memory (LSTM) architecture with the reinforcement learning‐based Deep Deterministic Policy Gradient (DDPG) algorithm. The proposed method predicts the teleoperator's angular and linear controlling commands by using data gathered by embedded sensors on the specially designed and built telepresence robot. Simulations and experiments assess the operation of the proposed technique in Gazebo simulation and MATLAB with robot operating system (ROS) integration, which shows 2.3% better response in the presence of static.

Abstract Transformers have been widely used in various computer vision applications. Compared to traditional convolutional neural networks (CNNs), transformer's inference includes plenty of non‐linear operations, such as softmax and Gaussian error linear units (GELU). As the scale of transformers grows, an efficient hardware implementation of these operations is significant. However, the current works of computer vision neural network accelerators focus on CNN and less attention is paid to transformer. In addition, most current FPGA‐based softmax or GELU accelerators are not designed for vision transformer (ViT). To solve this problem, this work proposes a high speed reconfigurable accelerator. The architecture can support both softmax and GELU functions in ViT by reconfiguring the data path. This architecture on Xilinx XCVU37P is implemented through mathematical transformation and hardware optimization design, and achieve the performance of 102.4 Giga bits per second (Gbps) at 200 MHz. Experimental results show that the architecture achieves a very small accuracy loss in the ViT's…

Abstract This work aims to identify cancerous (malignant) and non‐malignant (non‐cancerous) cells in a breast cancer database. Wisconsin breast cancer data (WBC) was utilized and obtained from the University of California, Irvine's machine learning repository. The proposed approach involves the Naive bayes algorithm with Gaussian distribution of the function in combination with Chi‐squared‐based attributes selection approach. This experimentation has been done after reducing the dimensional space of the used data with extended Kernel Principal Component Analysis (K‐PCA). Five different kernels in K‐PCA have been tested after the implementation of necessary pre‐processing techniques. The performance assessment of the proposed system has been evaluated based on confusion matrix‐based accuracy, precision, sensitivity, and specificity. Our proposed methodology with six selected feature and sigmoid K‐PCA attained the best accuracy of 99.28%. This result outer performs many state‐of‐the‐art studies recently published on the identical dataset.

Abstract Convolutional neural networks (CNN) have a strong feature extraction ability for images and present a high level of efficiency and accuracy in object detection and image recognition. When CNN is used to model microwave devices, the existing literature generally uses its size parameters as one‐dimensional (1‐D) input, which does not give full play to the image‐processing ability of CNN. In order to make full use of the characteristics of CNN, this letter converts the 1‐D input of microwave devices into the form of an image model, that is, the 1‐D input is transformed into a two‐dimensional (2‐D) matrix composed of 0 and 1 as the input. The image model is combined with CNN, called image‐based CNN (ICNN), which establishes a deep learning surrogate model between the physical parameters and electrical properties of microwave devices and improves the accuracy and generalization ability of the model. Taking the resonant frequency of the microstrip antenna as a simulation example, modelling was carried out by the proposed ICNN and compared with the mainstream machine learning…

Abstract This letter presents a new thin substrate‐integrated waveguide with twisted integrated–digitated capacitor‐based corrugations that offers a transmission loss < 0.55 dB. The presented waveguide operates at TE 10 mode and is used to present a wideband beam‐scanning leaky‐wave antenna with an array of dumbbell‐shaped slots. The antenna is shown to operate at a frequency band of 25–37 GHz and offers a gain > 13 dBi throughout the frequency band. It has a frequency‐dependent beam‐scanning capability of 6 deg/GHz. The proposed antenna being thin is extremely conformal and is suitable for applications in millimetre‐wave off‐body communication.

Abstract The paper presents a new practical design for a 4 × 1 planar switched array of dielectric filled waveguide antennas loaded with bow‐tie shaped slots operating at 26.5 to 29.5 GHz for 5G millimetre‐wave applications. The design is realized as a three‐layered architecture, with the top layer behaving as a radiator, the bottom layer as a feed network and a control circuit; and a common ground plane in the middle layer, offering a small form factor. The bow‐tie slots are used to achieve suitable bandwidth with a stable gain of ∼ 13 dBi. The proposed dielectric filled waveguide (DFW) is shown to offer a 5 deg/GHz freq.‐controlled beam‐sweep and a 70° fixed freq. beam‐steer. With only three switching ICs, it offers low power consumption and fast beam‐steering. Further, a combination of freq.‐controlled beam‐scanning and fixed‐freq. beam‐steering allows for a wide coverage of the antenna.

Abstract Intrusion Detection System (IDS) is a critical cybersecurity task that involves monitoring network traffic for malicious activity and taking appropriate action to stop it. However, insufficient training data or improperly chosen thresholds often limit the accuracy of such systems, resulting in high false‐positive rates. To improve the accuracy of an IDS, blockchain technology can be used as it provides a secure, decentralized, immutable ledger that can track suspicious activity over time and also identify intrusions globally. In this paper, the authors propose a novel methodology to improve the accuracy of blockchain‐based IDS. The approach combines different intrusion detection algorithms using a blockchain‐integrated architecture. It is based on the fusion principle and weighted votes, which the authors used to determine their results. The authors tested the system on DARPA 99 and MIT‐Lincoln Labs datasets using accuracy and false‐positive rate as their two metrics. The system achieved 92.6% accuracy and 7.4% false‐positive rates, indicating that the proposed system…

Abstract Vector Quantization (VQ) is a clustering problem in the fields of signal processing, source coding, information theory etc. Taking advantage of recent advances in the field of deep neural networks, this paper investigates the performance between VQ clustering problems and deep neural networks. A k ‐means‐based deep network architecture for VQ is presented to solve clustering problems. By applying the deep learning implementation of convergence optimization, a clustering neural network (algorithm) for the purpose of VQ is proposed. In practice, the proposed network quantifies the vectors over a set of stacked neural layers, overcoming the exponential complexity problem of VQ methods by trainable parameters. Experiments show that the work can improve the results without human intervention, and outperforms traditional clustering methods modified for VQ.

Abstract This study investigates the development of InAs quantum dot (QD) lasers on a InP(001) substrate, utilizing only III‐arsenide layers. This approach avoids the issues associated with the use of phosphorus compounds, which are evident in the crystal growth of conventional C/L‐band QD lasers, making the manufacturing process safer, simpler, and more cost‐effective. The threshold current density of the fabricated QD laser was 633 A/cm 2 , which is the lowest value for QD lasers in the 1.6‐µm wavelength region. This result suggests a high cost‐effectiveness and paves the way towards a large‐scale production technology for high‐performing C/L/U‐band QD lasers.

Abstract The ideality factor of a diode gives the information on the current conduction or recombination processes occurring inside the device. The ideality factor obtained from the electrical current–voltage ( I–V ) characteristics by the conventional method is typically masked by the effect of the series resistance at high currents. In this study, from a careful analysis of the I–V characteristics, a new formula that can extract the inherent ideality factor without the effect of the series resistance is presented and experimentally tested with a blue light‐emitting diode. The new ideality factor thus obtained is compared with the one by the photovoltaic measurement.

Abstract Aiming at accelerating the inter coding of versatile video coding (VVC), the existing deep‐learning‐based methods utilize a single convolutional neural network (CNN) to directly predict the quadtree plus multi‐type tree (QTMT)‐based partition of the whole coding tree unit (CTU). However, these methods adopt one prediction network for unevenly distributed CTUs and ignore that the different CTUs have different partition prediction difficulties, leading to performance degradation and computation waste. To overcome these limitations, a classification‐prediction joint framework is proposed to accelerate inter coding of VVC in this letter, which combines classification and prediction to process different CTUs through different networks with appropriate capacities. To achieve effective partition prediction of the whole CTU, the QTMT‐based partition is first modeled as the partition homogeneity map (PHM), which is a value map reflecting the partition of each 8× 8 unit. Second, the classification module classifies the CTUs into different classes according to their partition…

Abstract We propose a new concept millimetre‐wave patch antenna that integrates the functions of an antenna and a capacitive proximity sensor to detect the hand grip state for 5G mobile terminals and compensate for the hand effect. The proposed antenna has the structure of a proximity‐coupled fed patch and functions as a proximity sensor by using the capacitance change of the patch that occurs when the user's hand approaches the patch. By observing the capacitance change at the centre of the patch operating in the TM01 mode, it is possible to simultaneously perform the functions of antenna and sensor without mutual interference. The proposed antenna is implemented as a 1 × 4 array. The experimental results show that it has a stable gain of 8.3 to 10.1 dBi at 26.5 to 29.5 GHz and can operate as a proximity sensor with a capacitance change of 200 fF according to the proximity of the hand.

Abstract The authors report on a terahertz band wireless communication experiment employing a resonant tunneling diode receiver (Rx) and uni‐travelling carrier photodiode transmitter. An intermediate‐frequency based transmission facilitates a low‐complexity envelope‐detection type Rx architecture for complex‐modulated signals. Forward error correction recoverable data‐rates using quadrature phase shift keying modulation and 16‐level quadrature amplitude modulation are 60 and 68 Gbit/s, respectively.

Abstract Deep learning based image quality assessment models usually learn to predict image quality from a single dataset, leading the model to overfit specific scenes. To account for this, mixed datasets training can be an effective way to enhance the generalization capability of the model. However, it is nontrivial to combine different image quality assessment datasets, as their quality evaluation criteria, score ranges, view conditions, as well as subjects are usually not shared during the image quality annotation. Instead of aligning the annotations, this paper proposes a monotonic neural network for image quality assessment model learning with different datasets combined. In particular, this model consists of a dataset‐shared quality regressor and several dataset‐specific quality transformers. The quality regressor aims to obtain the perceptual quality of each image of each dataset and the quality transformer maps the perceptual quality to the corresponding annotation monotonically. The experimental results verify the effectiveness of the proposed learning strategy and the code…

Abstract Self‐rectifying memristor has no need for selector devices, but possesses the one‐way transmission behaviour and multi‐level non‐volatile memory characteristics, which makes it a promising candidate for electronic synapse. In this letter, the authors propose a novel self‐rectifying memristor based on a Pt/Hf 0.5 Zr 0.5 O 2 /TiN structure. The devices show large memory window (10 4 ) and high rectifying ratio (10 4 ), which can block the sneak current in a passive crossbar array without any additional hardware overhead. Moreover, the devices demonstrate excellent multi‐level states modulation capability, low power consumption, high endurance and long retention. The final benchmark demonstrates that the proposed Pt/Hf 0.5 Zr 0.5 O 2 /TiN self‐rectifying memristor is a promising candidate for electronic synapse application.

Abstract The presented paper proposes a photovoltaic module hot spot detection algorithm based on YOLOv8‐BCB. The algorithm addresses issues such as component efficiency degradation and poor contact in long‐term operation of PV systems, with a focus on the hot spot effect’. To achieve rapid detection and localization of small targets in complex scenes, the algorithm incorporates the Weighted Bi‐directional Feature Pyramid Network (BiFPN) into YOLOv8. Additionally, a lightweight upsampling operator called Content‐Aware ReAssembly of FEatures (CARAFE) is used to reduce the detection load on the unmanned aerial vehicle (UAV) detection system. The BiFormer attention mechanism is also integrated into the C2f module to better capture dependencies between sequences and reduce background interference. To highlight the superiority of the authors’ algorithm compared to other high‐quality algorithms, the authors conducted comparative experiments on the same dataset. The YOLOv8‐BCB algorithm surpasses the SSD, faster‐cnn, and RetinaNet algorithms in both accuracy and detection speed. It…

Abstract Single‐mode distributed feedback GaSb‐based interband cascade lasers with record emission beyond 6.1 µm are presented. The results are based on an epitaxial design with reduced resonant intersubband absorption in the valence band and rebalanced internally generated carriers. The epi‐down mounted 8 µm wide and 1 mm long laser chip is operated in continuous wave mode at room temperature and covers a bandwidth of over 20 nm with temperature and current tuning. At 25°C more than 4 mW of optical output power was measured.

Abstract The generation of a 24‐fs fibre‐coupled electro‐optic‐modulation (EO) comb at 1.5 μm with a 25‐GHz repetition rate, which is the shortest pulse, is demonstrated. The authors also generated a 2/3‐octave spanning supercontinuum spectrum using precise dispersion‐controlled silicon nitride waveguides. This method can open new horizons to generate a compact and robust carrier‐envelope‐offset‐locked EO comb.

Abstract Interrupted sampling repeater jamming (ISRJ) is a novel intra‐pulse coherent jamming based on digital radio frequency memory (DRFM). By repeatedly sampling and retransmitting the radar transmitting signal fragments, a series of false targets can be formed after pulse compression (PC), posing a severe threat to modern radar systems. Inspired by the energy function method and histogram analysis in image processing, an adaptive time‐frequency (TF) filtering method is proposed in this letter. The ISRJ‐contaminated regions can be accurately determined in the TF image after histogram analysis and subsequent energy accumulation. Guided by the energy function, the proposed method can automatically adjust the intensity threshold in TF image histogram analysis and therefore reveals better robustness compared with other competing methods. Simulations have verified the effectiveness and robustness of the proposed method against ISRJ under various circumstances.

Abstract Newborn infants are exposed to painful experiences, routinely practised clinically, that might increase their short‐ and long‐term morbidity and mortality. Facial expression has been widely used in clinical practice to assess pain in newborns. However, the inherent human visual attention required to make such vital inference is poorly understood. It is also unknown whether this inference occurs differently when comparing health professionals with non‐health ones. To investigate these issues, the authors have recorded and monitored the pupil size signal of 102 subjects (44 experts, 29 parents, and 29 non‐experts) while visually analyzing 20 frontal face images of 10 distinct newborns after a painful procedure (positive stimulus) and at painless rest (negative stimulus). Our experimental results show that neonatal pain assessment is more cognitively demanding when analyzing the presence of pain rather than its absence. In addition, the pupil responses for both positive and negative stimuli and all sample groups of subjects present experimentally a common temporal pattern,…

Abstract This letter presents a hardware demonstrator of an all‐SiC three‐level T‐type (3LTT) inverter with the common‐mode (CM) EMI filter stages placed on the DC input instead of the AC output side, targeting, for example, high‐efficiency PV applications. The extensive experimental characterization shows that state‐of‐the‐art SiC transistors and a DC‐side CM filter enable an unprecedented peak/full‐load efficiency of 99.4% (calorimetric measurement) at 12.5 kW and a power density of 2.4 kW/dm 3 (39 W/in 3 ). The demonstrator fulfills CISPR 11 Class A EMI regulations as well as upcoming EMI standards for the frequency range of 9–150 kHz. Compared to other high‐efficiency converters, which often employ bridge legs with more output voltage levels, the described 3LTT concept thus offers a very favorable trade‐off between complexity and performance.

Abstract Over the past two decades, the number of people with arm disabilities has dramatically increased. Many researchers have begun to concentrate on developing technologies to address this challenge. Exoskeleton is one of the most successful technologies out of these since it does not require medical staff to accompany the patients and can continually rehabilitate the patients until they regain the ability to move voluntarily. However, the majority of exoskeletons are anchored to the ground and individuals are unable to purchase one due to its high manufacturing costs. Furthermore, since this type of exoskeleton is anchored to the ground, patients must go to hospitals to get rehabilitation services. In this study, a portable assistive exoskeleton for human arm motions is designed to address this problem. This device can carry patients' arms to the desired position by adhering to a prescribed trajectory by medical specialists. The main parts of this exoskeleton are made of polylactic acid and produced using 3D printing technology. Therefore, the total manufacturing costs of the…

Abstract In control theory, a controller parameter‐tuning method called virtual reference feedback tuning (VRFT) is proposed. VRFT can tune a feedback controller using single experimental data. If VRFT can be applied to a vehicle, the yaw‐rate controller can be adequately tuned without the need for a vehicle model. Therefore, this study expands the results of VRFT to realize the desired yaw‐rate control of autonomous vehicles. The key point of the proposed method is to realize the auto‐tuning of the gain‐schedule proportional–integral (PI) controller based on the vehicle velocity. In this study, the validity of the proposed method using a vehicle dynamics block set is verified.

Abstract This paper investigated the back‐barrier (BB) effect for gallium nitride (GaN)‐based high‐electron‐mobility transistors with an Fe‐doped buffer and Fe‐buffer + Indium gallium nitride (InGaN)‐BB structure. The authors found that the Fe‐doped buffer + InGaN‐BB structure was effective in reducing the off‐state leakage current compared to the Fe‐doped buffer. Secondary‐ion‐mass spectrometry measurements revealed that the segregated Fe existed with peaks at ∼2 × 10 17 cm −3 around the InGaN‐BB layer. The authors believe that the negative charges which are generated by Fe effectively increased the BB effect as they exist just underneath the 2‐dimensional‐electron‐gas channel and successfully achieved a high output power operation of 4.6 W/mm at 94 GHz.

Abstract In industrial recirculating aquaculture systems (IRAS), the autonomous decision control of feeding strategies remains a practical concern. Conventionally, control schemes were established from data‐driven view, which fails to comprehensively perceive activity status of fishes. To deal with this issue, a deep vision sensing‐based fuzzy control scheme is proposed for smart feeding in IRAS. In the first stage, a deep learning‐based object detection model is introduced to capture two aspects features as the decision factors: residual bait and eating frequency. In the second stage, a fuzzy neural network model is formulated to calculate control decision strategies via fuzzy inference. And experiments on real‐world visual scenes are conducted to verify the proposal.

Abstract As worldwide counterterrorism operations grow, screening people for concealed objects in public places utilizing Terahertz security technology is becoming increasingly critical. In this letter, a passive THz Human security image Intelligent detection method (HE‐DETR‐DC5) is proposed that combines histogram equalization (HE) processing and DEtection TRansformer (DETR). The proposed method first performs histogram equalization on passive THz images to improve image contrast. In addition, the cavity convolution is added to the ResNet‐50 backbone network to enhance the model's attention to the concealed object in the passive THz image and improve the accuracy. The corresponding model is called DETR‐DC5. The experimental results show that the average precision mAP of the proposed method can achieve 99.9%. At the same time, compared to other image enhancement methods, the histogram equalization method used in this letter has better performance and higher detection accuracy. The detection speed of the proposed method is about 0.5 FPS, which can meet the demand for real‐time…

Abstract Radio Frequency Fingerprinting (RFF) has been recently investigated by the research community to enhance wireless security. This letter proposes an RFF approach based only on the complex ramp‐up transient portion of the transmitted frame. The well known issues in literature with the use of the transients for RFF is that they have very short duration, they are strongly non‐stationary and their analysis is sensitive to noise. Then, this letter proposes the application of an ensemble of transforms to the original complex time domain representation in combination with Convolution Neural Network (CNN) to address these issues. To avoid the computing demanding calculation of all the considered transforms, a pre‐processing step based on feature extraction and filter feature selection is implemented to select the most discriminating transforms to reduce the input data to the CNN. The approach is applied to two public RFF data sets, where the complex transient ramp‐up have been extracted. The result shows that the proposed approach is able to obtain a classification accuracy higher…

Abstract The appearance of quantum computing in the short foreseeable future and its capability to break conventional cryptographic algorithms forces to change the paradigm of secure real‐time communications. Thus, government organizations, data centers, and enterprises among others are migrating their public key infrastructure towards using post‐quantum cryptography (PQC) algorithms in order to mitigate the security threats posed by quantum computers. This letter presents the first quantum resilient secure end‐to‐end communication link based on PQC algorithms operating between two data‐processing units DPU. Both data‐processing units employ on‐board ARM processors to perform the computationally expensive cryptographic building blocks—in that case CRYSTALS‐Kyber as a key encapsulation mechanism and CRYSTALS‐Dilithium for digital signature scheme in combination with advanced encryption standard with 256‐bit key.

Abstract This letter describes a novel window‐based approach to FIR filter design. The window is constructed on the use of equispaced Gaussian basis functions. Unlike other known window‐based methods that do not allow for a satisfactory degree of control over band edges, the proposed method affords very good solution for controlling critical frequencies. In addition, the proposed window method is easier to implement than Kaiser's and affords a better passband flatness than any known design approach. It also yields stopband attenuations and control of critical frequencies which turn out to be very close to those obtainable with Parks–McClellan's method. So the proposed GBR window approach appears to be a significant step forward.

Abstract AlGaAsSb attracts significant interest for near‐infrared avalanche photodiodes (APD). The authors report a two‐order reduction in the dark current and a six‐time enhancement of gain in random alloy (RA) AlGaAsSb APD that is surface passivated by conformal coating of Al 2 O 3 via atomic layer deposition (ALD). The dark currents of the APDs with 400‐µm diameter (dry etched) at 90% breakdown voltage (0.9 V br ) are (5.5 ± 0.5) × 10 −5 A, (2.1 ± 0.4) × 10 −5 A, and (6.2 ± 0.8) × 10 −7 A for non‐passivated, Si 3 N 4 passivated, and Al 2 O 3 passivated devices, respectively. The dark current at a gain of 10 for the Al 2 O 3 passivated device is 1 × 10 −8 A which is comparable to the reported value for 100‐µm diameter mesa diodes passivated by SU‐8. Maximum gain values of 6, 12, and 35 were obtained for non‐passivated, Si 3 N 4 passivated, and Al 2 O 3 passivated devices, respectively. Moreover, punch‐through capacitance of 8 pF in a spectral response of 450 to 850 nm was obtained. Thus, Al 2 O 3 passivation can be the best solution for antimonide optoelectronic devices.

Abstract Pseudo‐random number generators (PRNGs) are the cornerstone of various fields including computer science, cryptography, and scientific simulation. To generate high‐quality and unpredictable pseudo‐random sequences, many works draw attention to the use of chaos theory and dynamical systems. However, most of them focus on continuous or low‐dimensional chaotic systems with strong temporal correlations or insufficient nonlinear dynamics. Thus, in this study, a new PRNG based on a four‐dimensional discrete system is proposed to solve the aforementioned flaws. The PRNG has been implemented on Xilinx Artix‐7 xc7a100tfgg484‐2, which can generate pseudo‐random sequences at a high speed of 12811.53 Mb/s without additional post‐processing. All these sequences have successfully passed the NIST SP800.22 standard test. Both throughput and randomness quality of the proposed PRNG outperform the state‐of‐the‐art.

Abstract The authors propose and experimentally demonstrate an on‐chip all‐optical multicasting (AOM) for 40 Gbit/s mode‐division‐multiplexed quadrature phase‐shift keying (MDM‐QPSK) signals based on a parallel dispersion‐engineered multimode non‐linear silicon waveguide. Five dual‐mode multicast wavelengths are successfully obtained on the generate idlers, and the power penalties of all the multicast channels are less than 1.1 dB at the bit error rate (BER) of 3.8 × 10 −3 . The dual‐mode AOM scheme has the potential to promote the ability of optical cross‐connect in practical hybrid multiplexed networks including MDM channels.

Abstract This paper proposes a background calibration scheme for the pipelined‐Successive Approximation Register (SAR) Analog‐to‐Digital Converter (ADC) based on the neural network. Due to the non‐linear function fitting capability of the neural network, the linearity of the ADC is improved effectively. However, the hardware complexity of the neural network limits its application and promotion in ADC calibration. Hence, this paper also presents the optimization schemes, including the neuron‐based sharing neural network and the partially binarized with fixed neural network, in terms of calibration architecture and algorithm. A 60 MS/s 14‐bit pipelined‐SAR ADC prototyped in 28‐nm technology is utilized to verify the feasibility of the proposed calibration method. The measurement results show that the proposed calibration greatly enhances the Spurious Free Dynamic Range (SFDR) and Signal‐to‐Noise‐and‐Distortion Ratio (SNDR) from low frequency to Nyquist frequency. Meanwhile, the original calibrator and improved calibrator are synthesized in Synopsys Design Compiler to compare their…

Abstract Polarization dynamics in spin‐polarized vertical‐cavity surface‐emitting lasers (spin‐VCSELs) with high birefringence have recently been demonstrated to offer very high potential for optical data‐transmission systems that outperform their counterparts based on conventional direct current modulation by far. For polarization dynamics in spin‐VCSELs, the birefringence determines the resonance frequency and thus the modulation bandwidth. In previous work, birefringence was controlled using mechanical strain, which lacks the ability to be integrated in standard VCSEL manufacturing processes. In this work the polarization dynamics of a VCSEL with an integrated birefringence control mechanism is demonstrated based on custom designed integrated surface gratings. It is found that, despite the surface grating which is commonly known to stabilize the polarization, the presented spin‐VCSELs are able to generate polarization oscillations with frequencies corresponding to the birefringence induced by the surface grating and show polarization dynamics up to 68 GHz.

A common 400V dc bus for industrial motor drives advantageously allows the use of high-performance 600V power semiconductor technology in the inverter drive converter stages and to lower the rated power of the supplying rectifier system. Ideally, this supplying rectifier system features unity power factor operation, bidirectional power flow and nominal power operation in the three-phase and the single-phase grid. This paper introduces a novel bidirectional universal single-/three-phase-input unity power factor differential ac-dc converter suitable for the above mentioned requirements: The basic operating principle and conduction states of the proposed topology are derived and discussed in detail. Then, the main power component voltage and current stresses are determined and simulation results in PLECS are provided. The concept is verified by means of experimental measurements conducted in both three-phase and single-phase operation with a 6kW prototype system employing a switching frequency of 100 kHz and 1200V SiC power semiconductors.

Abstract An improved coot optimization algorithm (COOT) is proposed for the coverage optimization in wireless sensor networks (WSNs). To monitor areas of interest and obtain valid data, a WSNs coverage model is developed. The population is initialized with a Cubic map and an opposition‐based learning strategy. Carrying out dimension‐by‐dimensional opposition‐based learning on the leader population to strengthen the global search ability of the algorithm, the simplex method is introduced to optimize the local exploration of the population. The experimental results demonstrate that the enhanced COOT can effectively reduce energy consumption and improve network coverage. A COOT based on simplex method and dimension‐by‐dimension opposition‐based learning is proposed to optimize the coverage of WSNs. The experimental results as Figure 2a and 2c show that the improved algorithm has faster convergence speed and higher precision, which reduces the node redundancy in the coverage optimization process of wireless sensor network and improves the coverage.

Abstract This article reports radio frequency characteristics of 150‐nm gate aluminum gallium nitride (AlGaN)/gallium nitride (GaN) high electron mobility transistors (HEMTs) fabricated using i ‐line stepper lithography and a thermal reflow technique. The authors have developed two different gate structures that were a field‐plated gate using the lift‐off process and a Y‐shaped gate using the ion‐milling process. Fabricated HEMTs using these different gate structures exhibited nearly equivalent DC characteristics. The field‐plated gate device showed a unity current gain cutoff frequency ( f T ) of 35 GHz and a maximum oscillation frequency ( f max ) of 106 GHz, while the Y‐shaped gate device showed f T of 36 GHz and f max of 115 GHz. The equivalent circuit analysis indicated a decrease in the gate‐drain capacitance and the drain conductance is responsible for the improved f max in the Y ‐shaped gate device.

Abstract Recently, flame detection has attracted great attention. However, existing methods have the issues of low detection rates, high false alarm rates, and lack of smoke anti‐interference ability. In this letter, a novel dynamic attention‐based network (DANet) is proposed for autonomous flame detection in various scenarios. To mitigate the disturbance of smoke in images, a dynamic attention strategy is proposed to discover the potential features among scale‐awareness and spatial‐awareness. Then, based on dynamic attention module, a decoupled detection head is presented, which can predict category, regression, and object score independently to boost the performance. A self‐contained challenging flame dataset, which is multi‐scene, multiscale, and multi‐interference informative is constructed to evaluate the proposed model and organize the experiments. Extensive ablation and comparison studies on self‐labelled dataset reveal the effectiveness of the proposed dynamic attention‐based network.

Abstract Coprime array can provide high degrees of freedom by using difference–sum co‐array under the same physical sensors, and can estimate the source under uncertain conditions. A special coprime array structure is proposed in this paper. Its difference–sum co‐array can improve the degrees of freedom. Finally, the proposed array structure estimation is used for direction‐of‐arrival. Simulation results and analysis show that the proposed array structure can effectively improve the accuracy of direction‐of‐arrival estimation. Under the same signal‐to‐noise ratio and snapshot number, it has lower root mean square error and higher estimation accuracy than other methods.

Abstract Hand reconstruction is the foundation of virtual reality and human–computer interaction, but currently it still faces challenges such as blurred interaction edge and inter‐hand occlusion. To solve these challenges, in this letter, the authors propose a framework called Multilevel Two Hand Interactive Former (MTHI‐Former) which considers the vertices of a hand model as graph structures and learn the connectivity relationships information between vertices. In this framework, the authors introduce two novel modules. The first is the Multi‐branch Image Feature Extraction Module , which is utilized to obtain accurate hand features. The second is the Multilevel Two Hand Interaction Module , which is utilized to fuse interactive hand information to enhance the attention features of interactive edges, and fuse vertex relationships to determine the occlusion relationship between interactive hands. The authors compare their method with recent methods on the InterHand 2.6M dataset, and the experimental results show that their method outperforms other representative methods, achieving…

Abstract This letter presents a compact penta‐band microstrip slot antenna. The proposed antenna comprises a microstrip feed line on the top plane, a polytetrafluoroethylene (PTFE) substrate, and a slotted ground plane. Different shapes of slots and two pairs of horizontal strips on the ground are introduced to achieve five frequency bands. A prototype is fabricated and measured to demonstrate the validity of the design. According to the measured result, the fabricated antenna can operate at five operating frequencies with an impedance bandwidth of 2.41–2.55 GHz (5.65%) for Bluetooth and WLAN, 3.31–3.58 GHz (8.14%) for WiMAX and Sub‐6 GHz 5G applications, 4.52–4.76 GHz (5.17%) for radiometry, 5.10–6.20 GHz (19.47%) for WLAN and ITS, and 10.14–12.40 GHz (20.10%) for radar applications. Moreover, the proposed antenna shows a bi‐directional radiation pattern at each operating band.

Abstract The authors present exploitation of Multiple Views in Single‐Path (MVSP) Synthetic Aperture Sonar (SAS). The authors demonstrate the interest of MVSP SAS for underwater Mine Counter‐Measures (MCM) with unmanned vehicles, to comply with requirements for performances of detection and classification and time constraints. The authors here lay the emphasis on exploitation in reduction of false alarms of classification by alleviating the ambiguity between mines and natural bottom objects. Finally, the authors show that MVSP SAS is offering a pre‐identification tool with high impact on MCM process duration.

Abstract A passive, low‐cost, paper‐based intelligent reflecting surface (IRS) is designed to reflect a signal in a desired direction to overcome non‐line‐of‐sight scenarios in indoor environments. The IRS is fabricated using conductive silver ink printed on paper with a specific nanoparticle arrangement, yielding a cost‐effective paper‐based IRS that can easily be mass‐produced. Full‐wave numerical simulation results were consistent with measurement results, demonstrating the IRS's ability to reflect incident waves into a desired nonspecular direction based on the inkjet‐printed design and materials.

Abstract Coherent change detection (CCD) takes advantage of the interferometric processing of synthetic aperture sonar (SAS) images and enables the detection of small scale changes to the scene between image pairs. This paper builds upon interferometric phase statistics developed for synthetic aperture radar and presents a method to differentiate between possible sources of decorrelation. A single‐pass pair of SAS images is categorized into four zones based on acoustic amplitude and coherence properties. Results suggest that regions of low coherence caused by a scene change can be differentiated from regions of low coherence due to other sources of decorrelation. Phase statistics could provide a technique to reduce the false alarm rate in CCD. Further studies are required to validate the approach for repeat‐pass SAS imagery and consider the effects of temporal decorrelation and misregistration errors on the phase distributions.

Abstract The advent of cloud computing, 5G, and artificial intelligence technology has spurred the exponential growth of big data and the need for data compression. To alleviate the CPU burden, computational engines for data compression integrated into network cards and storage devices, giving rise to computational storage. However, computational storage faces several challenges, such as limited memory resources for large hash tables, data dependency for parallel encoding and decoding, and stringent requirements for bandwidth, latency, and power efficiency. Here, an application‐specific integrated circuit‐based LZ77 solution that aims to address these challenges is proposed. Our solution reduces the hash table resource consumption and the bandwidth fluctuations, while achieving high compression ratios. The solution is implemented using Taiwan Semiconductor Manufacturing Company Limited 12 nm technology and demonstrate that a single LZ77 engine can achieve a 4 GB/s throughput at 1 GHz clock frequency. By using four engines, a computational storage drive to achieve 16 GB/s compression…

Abstract Due to their perfect periodic autocorrelation property, Zadoff–Chu sequences are often used as stimulus signals in the measurement of radio channel responses. In this letter, the cross‐correlation of a linear shift‐invariant system's response to a Zadoff–Chu sequence is derived for the case that a multiplicative perturbation such as phase noise is present at its output. The perturbation signal is shown to incur a spurious discrete Fourier transform, thus degrading the correlation's peak to sidelobe ratio. The implications for the performance limits of channel measurement systems are discussed.